Quantile regression: applications and current research areas
MetadataShow full item record
Quantile regression offers a more complete statistical model than mean regression and now has widespread applications. Consequently, we provide a review of this technique. We begin with an introduction to and motivation for quantile regression. We then discuss some typical application areas. Next we outline various approaches to estimation. We finish by briefly summarizing some recent research areas.
Showing items related by title, author, creator and subject.
Yu, K.; Lu, Zudi (2004)We consider non-parametric additive quantile regression estimation by kernel-weighted local linear fitting. The estimator is based on localizing the characterization of quantile regression as the minimizer of the appropriate ...
Austen, Siobhan; Jefferson, Therese; Ong, Rachel (2014)This study investigates the gender wealth gap in Australia by examining differences in the net worth of households headed by single women and men, using data from the 2006 Household, Income and Labour Dynamics in Australia ...
Tarverdimamaghani, Yashar; Rammohan, A. (2016)Globally, child mortality rates continue to be unacceptably high despite improvement in child health outcomes. The role of macro level indicators, such as governance and health aid on child mortality, remains under-researched. ...